Laszlo Koczy | Budapest University of Technology and Economics (original) (raw)
Papers by Laszlo Koczy
Both general fuzzy systems and most neural networks are universal approximators in the sense that... more Both general fuzzy systems and most neural networks are universal approximators in the sense that they are capable of approximating any continuous function with arbitrary accuracy with respect to, e.g., the supremum norm. It means that these techniques share approximation capabilities. However, the way they captures the underlying transfer function is different. Fuzzy systems operating with if-then rules have the advantage of easy linguistic interpretability, while neural networks can adapt learning methods to improve their performance according to a training data set. We point out in this paper that several fuzzy controllers implement one of the typical neural networks (having radial basis type activation functions), and hence, their combination may alloy the the advantageous properties of the two techniques.
Page 1. Behaviour based techniques in user adaptive Kansei technology Szilveszter KOVÁCS, Naoki K... more Page 1. Behaviour based techniques in user adaptive Kansei technology Szilveszter KOVÁCS, Naoki KUBOTA, Katsutoshi FUJII, László T. KÓCZY* Gifu Prefectural Research Institute of Manufacturing Information Technology ...
Page 1. Kovács, Sz., Kóczy, LT: The use of the concept of vague environment in approximate fuzzy ... more Page 1. Kovács, Sz., Kóczy, LT: The use of the concept of vague environment in approximate fuzzy reasoning, Fuzzy Set Theory and Applications, Tatra Mountains Mathematical Publications, Mathematical Institute Slovak Academy ...
Page 1. Sz. Kovács, N. Kubota, K. Fujii and LT Kóczy: Interpolative Fuzzy Reasoning and Fuzzy Aut... more Page 1. Sz. Kovács, N. Kubota, K. Fujii and LT Kóczy: Interpolative Fuzzy Reasoning and Fuzzy Automata in Kansei Technology, Proceedings of the AFSS2000, the Fourth Asian Fuzzy Systems Symposium, pp.335-340, May 31-June 3, Tsukuba, Japan, (2000). Draft version. ...
Page 1. 23 THE CONVEXITY AND PIECEWISE LINEARITY OF THE FUZZY CONCLUSION GENERATED BY LINEAR FUZZ... more Page 1. 23 THE CONVEXITY AND PIECEWISE LINEARITY OF THE FUZZY CONCLUSION GENERATED BY LINEAR FUZZY RULE INTERPOLATION László T. Kóczy LIFE Chair of Fuzzy Theory Dept. of System Science, Tokyo ...
Hirotsugu Sakuragi, Wai-keung Fung, Péter Baranyi, Szilveszter Kovács, Masaharu Sugiyama, László ... more Hirotsugu Sakuragi, Wai-keung Fung, Péter Baranyi, Szilveszter Kovács, Masaharu Sugiyama, László T. Kóczy Gifu Prefectural Research Institute of Manufactural Information Technology 4-179-1 Sue Kakamigahara Gifu 509-0108 Japan Tel:+ 81-583-79-2207; Fax:+ 81-583-79-2208; E-mail: sakuragi@ gifu-irtc. go. jp, wkfung@ mae. cuhk. edu. hk, baranyi@ ttt-202. ttt. bme. hu, szkszilv@ gold. uni-miskolc. hu, sugi@ gifu-irtc. go. jp, koczy@ fuzzy. ttt. bme. hu Key Words: Virtual teaching, potential based guiding model
The main contribution of this paper is to overview and discusses possible applications of fuzzy r... more The main contribution of this paper is to overview and discusses possible applications of fuzzy relational calculus to solve some issues and challenges of recommender systems. The presented ideas are targeting the most essential aspects of these problems, the knowledge representation and handling.
Page 1. Kovács, Sz., Kóczy, LT: Application of an approximate fuzzy logic controller in an AGV st... more Page 1. Kovács, Sz., Kóczy, LT: Application of an approximate fuzzy logic controller in an AGV steering system, path tracking and collision avoidance strategy, Fuzzy Set Theory and Applications, Tatra Mountains Mathematical ...
... Szilveszter Kovacs Department of Information Technology, University of Miskolc, Miskolc-Egyet... more ... Szilveszter Kovacs Department of Information Technology, University of Miskolc, Miskolc-Egyetemvaros, Miskolc, H-35 15, Hungary E-mail: szkovacs@iit.uni-miskolc.hu ...Szilveszter Kovacs is supported by the Gyorgy Bektsy Postdoctoral Scholarship. ...
Page 1. Kovács, Sz., Kóczy, LT: Approximate Fuzzy Reasoning Based on Interpolation in the Vague E... more Page 1. Kovács, Sz., Kóczy, LT: Approximate Fuzzy Reasoning Based on Interpolation in the Vague Environment of the Fuzzy Rulebase as a Practical Alternative of the Classical CRI, Proceedings of the 7th International Fuzzy ...
International Journal of Reasoning Based Intelligent Systems, Mar 20, 2015
ABSTRACT This paper presents a method for optimising the parameters of fuzzy flip-flop-based neur... more ABSTRACT This paper presents a method for optimising the parameters of fuzzy flip-flop-based neural networks (FNN) consisting of fuzzy J-K and D flip-flop neurons based on various popular fuzzy operations using bacterial memetic algorithm with the modified operator execution order (BMAM). In early works, the authors proposed the Levenberg-Marquardt algorithm (LM) a widely used second order gradient type training algorithm for fuzzy neural networks variables optimisation. The BMAM local and global search evolutionary approach is a bacterial type memetic algorithm which executes several LM cycles during the bacterial mutation after each mutational step, using the LM method more efficiently. Numerical experiments were performed to show the function approximation capability of various quasi optimised FNN types based on fuzzy J-K and D flip-flop neurons using algebraic, Lukasiewicz, Yager, Dombi, Hamacher and Frank norms, trained with LM method and BMAM algorithm.
2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291), 2002
This paper discusses how training algorithms for determining membership functions in fuzzy rule b... more This paper discusses how training algorithms for determining membership functions in fuzzy rule based systems can be applied. There are several training algorithms, which have been developed initially for neural networks and can be adapted to fuzzy systems. In this paper the Levenberg-Marquardt algorithm is introduced, allowing the determination of an optimal rule base and converging faster than some more classic methods (e.g. the standard Back Propagation algorithm). The class of membership functions investigated is the trapezoidal one as it is general enough and widely used. The method can be easily extended to arbitrary piecewise linear function as well.
2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06), 2006
Hierarchical Fuzzy Signatures are generalizations of the Vector Valued Fuzzy Set concept introduc... more Hierarchical Fuzzy Signatures are generalizations of the Vector Valued Fuzzy Set concept introduced in the 1970s. A crucial question in the Fuzzy Signature context is what kinds of aggregations are applicable for combining data with partly different substructures. Our earlier work introduced the Weighted Relevance Aggregation method to enhance the accuracy of the final results of calculations based on Hierarchical
Both general fuzzy systems and most neural networks are universal approximators in the sense that... more Both general fuzzy systems and most neural networks are universal approximators in the sense that they are capable of approximating any continuous function with arbitrary accuracy with respect to, e.g., the supremum norm. It means that these techniques share approximation capabilities. However, the way they captures the underlying transfer function is different. Fuzzy systems operating with if-then rules have the advantage of easy linguistic interpretability, while neural networks can adapt learning methods to improve their performance according to a training data set. We point out in this paper that several fuzzy controllers implement one of the typical neural networks (having radial basis type activation functions), and hence, their combination may alloy the the advantageous properties of the two techniques.
Page 1. Behaviour based techniques in user adaptive Kansei technology Szilveszter KOVÁCS, Naoki K... more Page 1. Behaviour based techniques in user adaptive Kansei technology Szilveszter KOVÁCS, Naoki KUBOTA, Katsutoshi FUJII, László T. KÓCZY* Gifu Prefectural Research Institute of Manufacturing Information Technology ...
Page 1. Kovács, Sz., Kóczy, LT: The use of the concept of vague environment in approximate fuzzy ... more Page 1. Kovács, Sz., Kóczy, LT: The use of the concept of vague environment in approximate fuzzy reasoning, Fuzzy Set Theory and Applications, Tatra Mountains Mathematical Publications, Mathematical Institute Slovak Academy ...
Page 1. Sz. Kovács, N. Kubota, K. Fujii and LT Kóczy: Interpolative Fuzzy Reasoning and Fuzzy Aut... more Page 1. Sz. Kovács, N. Kubota, K. Fujii and LT Kóczy: Interpolative Fuzzy Reasoning and Fuzzy Automata in Kansei Technology, Proceedings of the AFSS2000, the Fourth Asian Fuzzy Systems Symposium, pp.335-340, May 31-June 3, Tsukuba, Japan, (2000). Draft version. ...
Page 1. 23 THE CONVEXITY AND PIECEWISE LINEARITY OF THE FUZZY CONCLUSION GENERATED BY LINEAR FUZZ... more Page 1. 23 THE CONVEXITY AND PIECEWISE LINEARITY OF THE FUZZY CONCLUSION GENERATED BY LINEAR FUZZY RULE INTERPOLATION László T. Kóczy LIFE Chair of Fuzzy Theory Dept. of System Science, Tokyo ...
Hirotsugu Sakuragi, Wai-keung Fung, Péter Baranyi, Szilveszter Kovács, Masaharu Sugiyama, László ... more Hirotsugu Sakuragi, Wai-keung Fung, Péter Baranyi, Szilveszter Kovács, Masaharu Sugiyama, László T. Kóczy Gifu Prefectural Research Institute of Manufactural Information Technology 4-179-1 Sue Kakamigahara Gifu 509-0108 Japan Tel:+ 81-583-79-2207; Fax:+ 81-583-79-2208; E-mail: sakuragi@ gifu-irtc. go. jp, wkfung@ mae. cuhk. edu. hk, baranyi@ ttt-202. ttt. bme. hu, szkszilv@ gold. uni-miskolc. hu, sugi@ gifu-irtc. go. jp, koczy@ fuzzy. ttt. bme. hu Key Words: Virtual teaching, potential based guiding model
The main contribution of this paper is to overview and discusses possible applications of fuzzy r... more The main contribution of this paper is to overview and discusses possible applications of fuzzy relational calculus to solve some issues and challenges of recommender systems. The presented ideas are targeting the most essential aspects of these problems, the knowledge representation and handling.
Page 1. Kovács, Sz., Kóczy, LT: Application of an approximate fuzzy logic controller in an AGV st... more Page 1. Kovács, Sz., Kóczy, LT: Application of an approximate fuzzy logic controller in an AGV steering system, path tracking and collision avoidance strategy, Fuzzy Set Theory and Applications, Tatra Mountains Mathematical ...
... Szilveszter Kovacs Department of Information Technology, University of Miskolc, Miskolc-Egyet... more ... Szilveszter Kovacs Department of Information Technology, University of Miskolc, Miskolc-Egyetemvaros, Miskolc, H-35 15, Hungary E-mail: szkovacs@iit.uni-miskolc.hu ...Szilveszter Kovacs is supported by the Gyorgy Bektsy Postdoctoral Scholarship. ...
Page 1. Kovács, Sz., Kóczy, LT: Approximate Fuzzy Reasoning Based on Interpolation in the Vague E... more Page 1. Kovács, Sz., Kóczy, LT: Approximate Fuzzy Reasoning Based on Interpolation in the Vague Environment of the Fuzzy Rulebase as a Practical Alternative of the Classical CRI, Proceedings of the 7th International Fuzzy ...
International Journal of Reasoning Based Intelligent Systems, Mar 20, 2015
ABSTRACT This paper presents a method for optimising the parameters of fuzzy flip-flop-based neur... more ABSTRACT This paper presents a method for optimising the parameters of fuzzy flip-flop-based neural networks (FNN) consisting of fuzzy J-K and D flip-flop neurons based on various popular fuzzy operations using bacterial memetic algorithm with the modified operator execution order (BMAM). In early works, the authors proposed the Levenberg-Marquardt algorithm (LM) a widely used second order gradient type training algorithm for fuzzy neural networks variables optimisation. The BMAM local and global search evolutionary approach is a bacterial type memetic algorithm which executes several LM cycles during the bacterial mutation after each mutational step, using the LM method more efficiently. Numerical experiments were performed to show the function approximation capability of various quasi optimised FNN types based on fuzzy J-K and D flip-flop neurons using algebraic, Lukasiewicz, Yager, Dombi, Hamacher and Frank norms, trained with LM method and BMAM algorithm.
2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291), 2002
This paper discusses how training algorithms for determining membership functions in fuzzy rule b... more This paper discusses how training algorithms for determining membership functions in fuzzy rule based systems can be applied. There are several training algorithms, which have been developed initially for neural networks and can be adapted to fuzzy systems. In this paper the Levenberg-Marquardt algorithm is introduced, allowing the determination of an optimal rule base and converging faster than some more classic methods (e.g. the standard Back Propagation algorithm). The class of membership functions investigated is the trapezoidal one as it is general enough and widely used. The method can be easily extended to arbitrary piecewise linear function as well.
2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06), 2006
Hierarchical Fuzzy Signatures are generalizations of the Vector Valued Fuzzy Set concept introduc... more Hierarchical Fuzzy Signatures are generalizations of the Vector Valued Fuzzy Set concept introduced in the 1970s. A crucial question in the Fuzzy Signature context is what kinds of aggregations are applicable for combining data with partly different substructures. Our earlier work introduced the Weighted Relevance Aggregation method to enhance the accuracy of the final results of calculations based on Hierarchical